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Algorithmic Trading in Experimental Markets with Human Traders: A Literature Survey
Neugebauer, Tibor; Nekrasova, Elizaveta; Bao, Te et al.
2022In Fullbrunn, Sascha (Ed.) Handbook of Experimental Finance
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Abstract :
[en] This chapter surveys the nascent experimental research on the interaction between human and algorithmic (bot) traders in experimental markets. We first discuss studies in which algorithmic traders are in the researcher’s hands. Specifically, the researcher assigns computer agents as traders in the market. We then followed it up by discussing studies in which the researcher allows human traders to decide whether to employ algorithms for trading or to trade by themselves. The paper introduces the types and performances of algorithmic traders that interact with human subjects in the laboratory, including zero-intelligent traders, arbitragers, fundamentalists, adaptive algorithms, and manipulators. We find that whether algorithm traders earn more profit than human traders crucially depends on the asset’s fundamental value process and the market environment. The potential impact of interactions with algorithms on the investor’s psychology is also discussed.
Disciplines :
Finance
Author, co-author :
Neugebauer, Tibor  ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
Nekrasova, Elizaveta ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
Bao, Te
Riyanto, Yohanes E.
External co-authors :
yes
Language :
English
Title :
Algorithmic Trading in Experimental Markets with Human Traders: A Literature Survey
Publication date :
October 2022
Main work title :
Handbook of Experimental Finance
Editor :
Fullbrunn, Sascha
Publisher :
Edward Elgar
Pages :
302-322
Peer reviewed :
Peer reviewed
Focus Area :
Finance
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since 04 November 2021

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